Proper timing of movements is crucial for many behaviors of living organisms. Disorders of temporal processing have been linked to neurological diseases, such as aphasia, dyslexia and Parkinson's disease. Neurophysiological studies revealed the involvement of many brain areas in temporal processing, but the neural mechanism of behavioral timing remains poorly understood. This is in part because previous studies examined brain regions in isolation, whereas temporal processing may be fundamentally distributed. To address this problem, we propose a study in which we will apply the methods of multielectrode recordings and neural interfaces to elucidate the mechanisms of motor timing and their plasticity in corticostriatal ensembles. We hypothesize that corticostriatal ensembles simultaneously encode temporal and spatial parameters of motor activities and facilitate learning of new temporal contingencies. This hypothesis will be tested through three specific aims: 1. Identify neural modulations in corticostriatal ensembles underlying temporal programming of movements and their plasticity during learning. Rhesus macaques will be implanted with multielectrode arrays in multiple cortical areas and the striatum. Monkey arm-reaching motor tasks will require both interval timing and directional programming. Novel instructions will be used to introduce learning paradigms. We expect to find that spatial and temporal components of motor tasks are processed and modified conjointly by the corticostriatal system. 2. Develop neural decoders that extract spatial and temporal information from corticostriatal ensembles. We will use neural decoding algorithms (Wiener filter, Kalman filter, discriminant analysis and Markov chains) to extract both temporal and spatial characteristics of motor patterns from large populations of cortical and striatal neurons. We expect to find that overlapping populations of neurons contribute to the extraction of both temporal and spatial characteristics. 3. Develop a real-time paradigm in which temporal and spatial motor behaviors are learned and controlled through a neural interface. Rhesus macaques will perform the same tasks as in Aim 1, but through a neural interface which will use decoding algorithms developed in Aim 2. We expect that corticostriatal ensembles will plastically adapt to this direct brain control. As the outcome of the proposed study we expect to have uncovered essential features of corticostriatal control of temporal sequencing of movements and neural plasticity involved. Moreover, we expect to have created an interface that extracts temporal and spatial parameters of movements in real time. These findings will contribute to therapies of neurological disorders of temporal processing and to neural prosthetics that reproduce decoded motor patterns in assistive devices.